Which of the following is a wrong statement regarding Gene Prediction Using Markov Models and Hidden Markov Models?

A zero-order Markov model assumes each base occurs independently with a given probability

Markov models and HMMs can be very helpful in providing finer statistical description of a gene

A Markov model describes the probability of the distribution of nucleotides in a DNA sequence

In a Markov model the conditional probability of a particular sequence position depends on k alternate positions

A zero-order Markov model assumes each base occurs independently with a given probability

Explore topic-wise MCQs in Bioinformatics.

This section includes 4 Mcqs, each offering curated multiple-choice questions to sharpen your Bioinformatics knowledge and support exam preparation. Choose a topic below to get started.

1.	Because a protein-encoding gene is composed of nucleotides in triplets as codons, more effective Markov models are built in sets of three nucleotides, describing nonrandom distributions of trimers or hexamers, and so on.
A.	True
B.	False
Answer» B. False

Discussion

2.	The use of Markov models in gene finding exploits the fact that oligonucleotide distributions in the coding regions are different from those for the noncoding regions.
A.	True
B.	False
Answer» B. False

Discussion

3.	Which of the following is a wrong statement regarding Gene Prediction Using Markov Models and Hidden Markov Models?
A.	Markov models and HMMs can be very helpful in providing finer statistical description of a gene
B.	A Markov model describes the probability of the distribution of nucleotides in a DNA sequence
C.	In a Markov model the conditional probability of a particular sequence position depends on k alternate positions
D.	A zero-order Markov model assumes each base occurs independently with a given probability
Answer» D. A zero-order Markov model assumes each base occurs independently with a given probability

Discussion

4.	The conventional determination of open reading methods identify only typical genes and tend to miss atypical genes in which the rule of codon bias is not strictly followed.
A.	True
B.	False
Answer» B. False

Discussion

Explore topic-wise MCQs in Bioinformatics.

Because a protein-encoding gene is composed of nucleotides in triplets as codons, more effective Markov models are built in sets of three nucleotides, describing nonrandom distributions of trimers or hexamers, and so on.

The use of Markov models in gene finding exploits the fact that oligonucleotide distributions in the coding regions are different from those for the noncoding regions.

Which of the following is a wrong statement regarding Gene Prediction Using Markov Models and Hidden Markov Models?

The conventional determination of open reading methods identify only typical genes and tend to miss atypical genes in which the rule of codon bias is not strictly followed.